Test-retest reliability of the default mode network in a multi-centric fMRI study of healthy elderly: Effects of data-driven physiological noise correction techniques

Camillo Marra, Paolo Maria Rossini, Rocco Marchitelli, Ludovico Minati, Moira Marizzoni, Beatriz Bosch, David Bartrés-Faz, Bernhard W. Müller, Jens Wiltfang, Ute Fiedler, Luca Roccatagliata, Agnese Picco, Flavio Nobili, Oliver Blin, Stephanie Bombois, Renaud Lopes, Régis Bordet, Julien Sein, Jean-Philippe Ranjeva, Mira DidicHélène Gros-Dagnac, Pierre Payoux, Giada Zoccatelli, Franco Alessandrini, Alberto Beltramello, Núria Bargalló, Antonio Ferretti, Massimo Caulo, Marco Aiello, Carlo Cavaliere, Andrea Soricelli, Lucilla Parnetti, Roberto Tarducci, Piero Floridi, Magda Tsolaki, Manos Constantinidis, Antonios Drevelegas, Peter Schönknecht, Tilman Hensch, Karl-Titus Hoffmann, Joost P. Kuijer, Pieter Jelle Visser, Frederik Barkhof, Giovanni B. Frisoni, Jorge Jovicich

Risultato della ricerca: Contributo in rivistaArticolo in rivista

22 Citazioni (Scopus)


Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within-site test-retest reliability and the across-site reproducibility consistency of DMN-derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue-based regression, PESTICA and FSL-FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z-scores and, albeit less markedly, the cluster-size in the DMN; in particular, FSL-FIX tended to increase the DMN z-scores compared to others. Within-site test-retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5-11% for DMN z-scores and cluster-size reliability. DMN pattern overlap was in the range 60-65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL-FIX and Tissue-based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC=0.67) for the DMN z-scores relative to NPC. Overall these findings support the use of rPNC methods like tissue-based or FSL-FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114-2132, 2016.
Lingua originaleEnglish
pagine (da-a)2114-2132
Numero di pagine19
RivistaHuman Brain Mapping
Stato di pubblicazionePubblicato - 2016


  • Anatomy
  • Default mode network
  • Independent component analysis
  • Multisite
  • Neurology
  • Neurology (clinical)
  • Physiological noise correction
  • Radiological and Ultrasound Technology
  • Radiology, Nuclear Medicine and Imaging
  • Resting-state networks
  • Task-free fMRI
  • Test-retest reliability

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